Hemodilution of bone marrow (BM) aspirates is a limitation of multiparameter flow cytometry (MFC) in plasma cell disorders. There is a need for a validated approach for assessing sample quality and the distribution of non-plasma cell BM populations by MFC could provide a solution. We evaluated BM-associated cell populations, assessed by next-generation flow cytometry (NGF) and white blood cell (WBC) count in 351 BM aspirated samples from 219 participants with plasma cell disorders in the Iceland Screens, Treats, or Prevents MM study (iStopMM), as markers of hemodilution by their discriminatory ability between first and (generally more hemodiluted) second pull BM aspirated samples. The most discriminating markers were used to derive a novel BM quality index (BMQI). Nucleated red blood cells and myeloid precursors provided the greatest discriminatory ability between first vs second pull samples (area under the curve (AUC): 0.87 and 0.85, respectively), significantly better than B cell precursors (AUC = 0.64; p < 0.001), mast cells (AUC = 0.65; p < 0.001), and the BM WBC count (AUC = 0.77; p < 0.05). We generated a novel BMQI that is intrinsic to current NGF protocols, for evaluating quality of diagnostic BM samples and suggest the use of a BMQI scoring system for interpreting results and guiding appropriate actions.
浆细胞癌多发性骨髓瘤在基因组特征、治疗反应及长期预后方面存在显著差异。为探究多发性骨髓瘤中的全局相互作用，我们将已知蛋白质相互作用网络与大规模临床注释数据集相结合。我们提出假设：基于基因表达、拷贝数变异和蛋白质相互作用的大规模相似性进行无偏倚网络分析方法，可能提供新的生物学见解。运用新型网络稳健性度量方法——奥利维-里奇曲率，我们分析了RNA测序基因表达与拷贝数变异数据模式及其与临床结局的关联。通过奥利维-里奇曲率进行的层次聚类分析，成功区分出具有较低无进展生存期的高危亚型。差异基因表达分析确定了118个表达显著异常的基因，这些基因虽既往未与多发性骨髓瘤建立关联，却与DNA修复、细胞凋亡及免疫系统功能密切相关。单变量分析发现其中8个基因（占118个的6.8%）具有预后价值，且均与免疫系统相关。网络拓扑分析识别出枢纽基因和桥梁基因，这些基因连接了已知具有多发性骨髓瘤生物学意义的关键基因。综上，多发性骨髓瘤基因相互作用网络分析通过创新的全局评估方法，揭示了与较短生存期相关的复杂免疫失调机制。
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